| Robust identification of noncoding RNA from transcriptomes requires phylogenetically-informed sampling S Lindgreen, SU Umu, ASW Lai, H Eldai, W Liu, S McGimpsey, ... PLoS computational biology 10 (10), e1003907, 2014 | 28 | 2014 |
| A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life SU Umu, PP Gardner Bioinformatics 33 (7), 988-996, 2017 | 23 | 2017 |
| A comprehensive profile of circulating RNAs in human serum SU Umu, H Langseth, C Bucher-Johannessen, B Fromm, A Keller, ... RNA biology 15 (2), 242-250, 2018 | 22 | 2018 |
| Avoidance of stochastic RNA interactions can be harnessed to control protein expression levels in bacteria and archaea SU Umu, AM Poole, RCJ Dobson, PP Gardner eLife 5, 2016 | 17 | 2016 |
| A probabilistic approach to microRNA-target binding H Oğul, SU Umu, YY Tuncel, MS Akkaya Biochemical and biophysical research communications 413 (1), 111-115, 2011 | 12 | 2011 |
| A high-resolution map of the human small non-coding transcriptome T Fehlmann, C Backes, J Alles, U Fischer, M Hart, F Kern, H Langseth, ... Bioinformatics 34 (10), 1621-1628, 2017 | 5 | 2017 |
| TaME-seq: An efficient sequencing approach for characterisation of HPV genomic variability and chromosomal integration S Lagström, SU Umu, M Lepistö, P Ellonen, R Meisal, IK Christiansen, ... Scientific reports 9 (1), 524, 2019 | 2 | 2019 |
| A meta-analysis of bioinformatics software benchmarks reveals that publication-bias unduly influences software accuracy PP Gardner, JM Paterson, FA Ghomi, SUU Umu, S McGimpsey, A Pawlik BioRxiv, 092205, 2017 | 2 | 2017 |
| Trainer: A general-purpose trainable short biosequence classifier H Oğul, A Kalkan, S Umu, M Akkaya Protein and Peptide Letters 20, 1108-1114, 2013 | 2 | 2013 |
| PO-096 Natural variation in serum small non-coding RNAs–potential biomarkers of cancer SU Umu, R Lyle, H Langseth, TB Rounge ESMO Open 3 (Suppl 2), A263-A264, 2018 | 1 | 2018 |
| TaME-seq S Lagström, SU Umu, M Lepistö, P Ellonen, R Meisal, IK Christiansen, ... Scientific Reports, 2019 | | 2019 |
| Circulating small non-coding RNAs associated with age, sex, smoking, body mass and physical activity TB Rounge, SU Umu, A Keller, E Meese, G Ursin, S Tretli, R Lyle, ... Scientific reports 8 (1), 17650, 2018 | | 2018 |
| PO-073 Small non-coding RNA in serum from testicular germ cell tumour patientsidentified by machine learning J Burton, H Hammer, S Umu, H Langseth, T Grotmol, T Grimsrud, ... ESMO Open 3 (Suppl 2), A255-A256, 2018 | | 2018 |
| Impact of age, sex, smoking, body mass and physical activity on circulating small non-coding RNA expression profiles TB Rounge, SU Umu, A Keller, E Meese, G Ursin, S Tretli, R Lyle, ... Cancer Research 78 (13 Supplement), 524-524, 2018 | | 2018 |
| Natural avoidance of stochastic mRNA: ncRNA interactions can be harnessed to control protein expression levels SU Umu, AM Poole, RCJ Dobson, PP Gardner bioRxiv, 033613, 2016 | | 2016 |
| Investigating prokaryotic transcriptomes and the impact of crosstalk between noncoding RNA and messenger RNA interactions SU Umu University of Canterbury, 2016 | | 2016 |
| mmDB: A repository of paired microRNA-messengerRNA expression profiles B Oğul, Y Tuncel, S Umu, M Akkaya, H Oğul 7th International Sympoisum on Health Informatics and Bioinformatics, 2012 | | 2012 |
| A Probabilistic Method for Prediction of microRNA-target Interactions. H Ogul, SU Umu, YY Tuncel, MS Akkaya IJCCI (NCTA), 289-293, 2011 | | 2011 |
Trine B RoungeCancer Registry of NorwayVerified email at kreftregisteret.no